ACMx: Estimation of Autoregressive Condtional Mean Models

In ConvFuncTimeSeries/test_t: Nonlinear time series analysis

Description

Estimation of autoregressive conditionl mean models with exogeneous variables.

Usage

ACMx(y, order = c(1, 1), X = NULL, cond.dist = "po", ini = NULL)

Arguments

y	time series of counts.
order	the order of ACM model.
X	matrix of exogenous variables.
cond.dist	conditional distributions. "po" for Poisson, "nb" for negative binomial, "dp" for double Poisson.
ini	initial parameter estimates designed for use in "nb" and "dp".

Value

ACMx returns a list with components:

data	time series.
X	matrix of exogenous variables.
estimates	estimated values.
residuals	residuals.
sresi	standardized residuals.

Examples

X=matrix(rnorm(100,100,1))
y=rpois(100,10)
ACMx(y,c(1,1),X,"po")

ConvFuncTimeSeries/test_t documentation built on May 29, 2019, 1:39 p.m.